Advanced Machine Learning Operations

In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Databricks Asset Bundles (DABs), Workflows, and Mosaic AI Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.

Skill Level

Professional

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

The user should have intermediate-level knowledge of traditional machine learning concepts, development, and the use of Python and Git for ML projects.
It is recommended that the user has intermediate-level experience with Python.

Outline

Overview of Machine Learning Operations on Databricks
Review of MLOps
Streamlining Development to Deployment
Continuous Workflows for Machine Learning Operations
Streamlining MLOps
Streamlining MLOps with Databricks
Testing Strategies with Databricks
Automate Comprehensive Testing
Model Rollout Strategies with Databricks
Model Quality and Lakehouse Monitoring
Introduction to Monitoring
Lakehouse Monitoring
Streamlining Multiple Environment Deployments - DABsBuild ML assets as CodeCourse Summary and Next Steps

Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	May 26	11 AM - 03 PM (Asia/Singapore)	-	English	$750.00
May 26	09 AM - 01 PM (America/New_York)	-	English	$750.00
Jun 23	08 AM - 12 PM (Asia/Kolkata)	-	English	$750.00
Jun 25	01 PM - 05 PM (Europe/London)	-	English	$750.00
Jul 22	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Jul 22	09 AM - 01 PM (America/New_York)	-	English	$750.00

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Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	May 26	11 AM - 03 PM (Asia/Singapore)	-	English	$750.00
May 26	09 AM - 01 PM (America/New_York)	-	English	$750.00
Jun 23	08 AM - 12 PM (Asia/Kolkata)	-	English	$750.00
Jun 25	01 PM - 05 PM (Europe/London)	-	English	$750.00
Jul 22	01 PM - 05 PM (Australia/Sydney)	-	English	$750.00
Jul 22	09 AM - 01 PM (America/New_York)	-	English	$750.00

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Upcoming Public Classes

Building Reliable Conversational Agents with Genie

This course teaches you how to design, build, and maintain a Databricks Genie Space, a natural language interface that enables business users to ask questions about governed data and receive SQL-backed answers without writing code.

You will learn how Genie fits into the Databricks AI/BI product family and how it translates natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Space that delivers accurate, consistent, and trustworthy results.

You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Space using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.

You will also learn how to share Genie Spaces with business users through Databricks One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.

By the end of the course, you will be able to create and manage a production-ready Genie Space that delivers governed, self-service conversational analytics at scale.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

Data Warehousing Practitioner

Data Warehousing with Databricks

This course is designed for data professionals who want to explore the data warehousing capabilities of Databricks. Assuming no prior knowledge of Databricks, it provides an introduction to leveraging Databricks as a modern cloud-based data warehousing solution. Learners will explore how use the Databricks Data Intelligence Platform to ingest, transform, govern, and analyze data efficiently using the industry-standard TCP-DI dataset as a reference. Learners will also explore Genie, an innovative Databricks feature that simplifies data exploration through natural language queries. By the end of this course, participants will be equipped with the foundational skills to implement and optimize a data warehouse using Databricks.

Languages Available: English | 日本語 | Português BR | 한국어

Apache Spark Developer

Monitoring and Optimizing Apache Spark Workloads on Databricks

This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.

Languages Available: English | 日本語 | 한국어